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Keywords = KPDN methods

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21 pages, 7512 KB  
Article
A Complex Network Important Node Identification Based on the KPDN Method
by Liang Zhao, Peng Sun, Jieyong Zhang, Miao Peng, Yun Zhong and Wei Liang
Appl. Sci. 2023, 13(14), 8303; https://doi.org/10.3390/app13148303 - 18 Jul 2023
Cited by 9 | Viewed by 2063
Abstract
In complex networks, identifying influential nodes is of great significance for their wide application. The proposed method integrates the correlation properties of local and global, and in terms of global features, the K-shell decomposition method of fusion degree is used to improve the [...] Read more.
In complex networks, identifying influential nodes is of great significance for their wide application. The proposed method integrates the correlation properties of local and global, and in terms of global features, the K-shell decomposition method of fusion degree is used to improve the actual discrimination degree of each node. In terms of local characteristics, the Solton index is introduced to effectively show the association relationship between each node and adjacent nodes. Through the analysis and comparison of multiple existing methods, it is found that the proposed method can identify key nodes more accurately so as to help quickly disintegrate the network. The final manual network verification also shows that this method is also suitable for the identification of important nodes of small-world networks and community networks. Full article
(This article belongs to the Special Issue Advances in Complexity Science through Modeling and Simulation)
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